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Bayesian Optimization based Nonlinear Adaptive PID Design for Robust Control of the Joints at Mobile Manipulators
In this paper, we propose to use a Nonlinear Adaptive PID controller to regulate the joint variables of a mobile manipulator. Motion of …
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Comparing the carbon costs and benefits of low-resource solar nowcasting
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Parallel MCMC Without Embarrassing Failures
Embarrassingly parallel Markov Chain Monte Carlo (MCMC) exploits distributed computing to scale Bayesian inference to large datasets by …
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Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
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Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels
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Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels
Discretization Drift in Two-Player Games
Gradient-based methods for two-player games produce rich dynamics that can solve challenging problems, yet can be difficult to …
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Discretization Drift in Two-Player Games
Riemannian Convex Potential Flows
Modeling distributions on Riemannian manifolds is a crucial component in understanding nonEuclidean data that arises, e.g., in physics …
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Riemannian Convex Potential Flows
Spectral Normalization for Deep Reinforcement Learning: an Optimisation Perspective
Most of the recent deep reinforcement learning advances take an RL-centric perspective and focus on refinements of the training …
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Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities
Advances in algorithmic fairness have largely omitted sexual orientation and gender identity. We explore queer concerns in privacy, …
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